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Databases · head to head

Apache Airflow vs EMQX

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
EMQX logo

EMQX

Databases

Erlang MQTT broker for large IoT fleets, relicensed to BSL with production free use limited to one node

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Apache Airflow self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job; EMQX the move to Business Source Licence 1.1 at version 5.9 in May 2025 limits free production use to a single node, so the clustering that justifies choosing EMQX now requires a paid subscription from the second node onward.
  • They diverge on capability: Apache Airflow covers Pipelines as Python, EMQX covers Erlang clustering.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Apache Airflow and EMQX actually diverge.

Attributes where Apache Airflow and EMQX differ
AttributeApache AirflowEMQX
Pricing modelOpen source, no licence fee; managed services billed separatelyPer month by connection and session volume
PlatformsLinux, Docker, Kubernetes, Self-hostedLinux, Docker, Kubernetes, Cloud, macOS

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Apache Airflow

  • Pipelines as Python
  • Web UI
  • Cloud provider packages
  • Jinja templating
  • Retries and dependencies
  • Extensible operators

Only in EMQX

  • Erlang clustering
  • MQTT 5.0 and QUIC
  • Rule engine
  • Data integration sinks
  • Session persistence
  • Multi protocol gateways
  • Authentication and authorisation
  • Dashboard and REST API

What people use each for

The jobs each tool is most often brought in to do.

Apache Airflow

  • Scheduling nightly ETL where step order and retries matternot EMQX
  • Coordinating machine learning training and evaluation runsnot EMQX
  • Orchestrating dbt runs alongside extraction and loadingnot EMQX
  • Replacing a sprawl of cron jobs with dependencies and visible run historynot EMQX

EMQX

  • A connected vehicle platform needing millions of persistent MQTT sessions with QUIC for handover across mobile networksnot Apache Airflow
  • An industrial operator routing sensor telemetry straight into TimescaleDB or Kafka without writing a consumer servicenot Apache Airflow
  • An IoT product team that has outgrown a single Mosquitto instance and needs clustering and shared subscriptionsnot Apache Airflow
  • A smart building deployment mixing MQTT, CoAP and LwM2M devices on one brokernot Apache Airflow

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Apache Airflow

  • Self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job
  • Built for scheduled batch work, and a poor fit for event-driven or sub-minute latency pipelines
  • Because DAGs are Python that the scheduler parses continuously, expensive top-level code in a DAG file slows the whole scheduler
  • Local development and testing of DAGs is awkward compared with newer orchestrators designed with it in mind

EMQX

  • The move to Business Source Licence 1.1 at version 5.9 in May 2025 limits free production use to a single node, so the clustering that justifies choosing EMQX now requires a paid subscription from the second node onward.
  • The relicensing arrived in a minor release, which caught users who had pinned to 5.x expecting Apache 2.0 terms and forced legal review of existing deployments.
  • Running an Erlang/OTP cluster well requires operational knowledge most teams do not have, and diagnosing distribution, mnesia or memory issues means learning a runtime you use for nothing else.
  • Enterprise pricing is quoted rather than published for the self-managed edition, so the cost of the clustered configuration you actually need is invisible until you talk to sales.
  • The Serverless tier caps at around a thousand connections and shares infrastructure, which makes it a prototyping tier rather than a genuine small production option.

Pricing, plan by plan

Apache Airflow

Free
  • Apache AirflowFree
    • Full scheduler and web UI
    • All provider packages
    • No task or DAG limits

EMQX

Free
  • Open Source single nodeFree
    • BSL 1.1 licence since version 5.9
    • Free production use of one node only
    • All former enterprise features visible
  • ServerlessFree
    • Free monthly quota then pay as you go
    • Up to 1,000 connections
    • 8 by 5 support
  • Dedicated Flex$234/month
    • Single tenant cluster
    • Traffic allowance included
    • 24/7 support
  • Enterprise self-managed$undefined/year
    • Deploy on premises, at the edge or in any cloud
    • Clustering licensed
    • 256 MB maximum message size

Which should you pick?

Choose Apache Airflow if

  • You need pipelines as python.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want web ui.
Apache Airflow review

Choose EMQX if

  • You need erlang clustering.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Cloud, macOS.
  • You also want mqtt 5.0 and quic.
EMQX review

Questions people ask

Is Apache Airflow or EMQX better?
Neither clearly leads. Apache Airflow starts at Free and EMQX at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or EMQX?
Apache Airflow starts at Free and EMQX at Free.
Does Apache Airflow or EMQX run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. EMQX runs on Linux, Docker, Kubernetes, Cloud, macOS.
Can I use Apache Airflow for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Airflow best used for?
Apache Airflow is most often used for scheduling nightly etl where step order and retries matter, coordinating machine learning training and evaluation runs, orchestrating dbt runs alongside extraction and loading, replacing a sprawl of cron jobs with dependencies and visible run history. Of those, scheduling nightly etl where step order and retries matter and coordinating machine learning training and evaluation runs are not what EMQX is typically brought in for.
What can Apache Airflow do that EMQX cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. EMQX covers Erlang clustering, MQTT 5.0 and QUIC, Rule engine, Data integration sinks.

Answered from the vendors’ own pages

Apache Airflow: Is Apache Airflow free?

Yes. Airflow is open source under the Apache Software Foundation with no licence fee. Costs are the infrastructure to run it, or a managed service such as Google Cloud Composer or Amazon MWAA.

EMQX: Is EMQX still open source?

Not in the OSI sense since version 5.9. It is source-available under Business Source Licence 1.1, reverting to Apache 2.0 four years after each release.

Apache Airflow: What language are Airflow workflows written in?

Python. A workflow is a Python file, so standard language features including loops and datetime handling can generate tasks dynamically, with no XML or command-line configuration.

EMQX: Can I run a free cluster?

No. The additional use grant permits free production use of one node; clustering requires a commercial licence.

Apache Airflow: Is Airflow suitable for real-time pipelines?

Not really. Airflow is designed for scheduled batch orchestration. Event-driven or sub-minute work is better served by a streaming platform such as Kafka or a purpose-built streaming engine.

EMQX: What changed for existing users?

Community and enterprise editions merged, so all features are now visible, but the licence terms tightened in the same minor release.

Apache Airflow: What are the main alternatives to Airflow?

Dagster and Prefect are the two most commonly weighed against it, both newer and both designed around the local development and testing experience Airflow is criticised for.

EMQX: Which version is still Apache 2.0?

Releases before 5.9 remain under Apache 2.0, and each BSL release converts to Apache 2.0 four years after publication.

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